Abstract

We propose a method to quantify narratives from textual data in a structured manner, and identify what we label "narrative monetary policy surprises" as the change in economic media coverage that can be explained by central bank communication accompanying interest rate meetings. Our proposed method is fast and simple, and relies on a Singular Value Decomposition of the different texts and articles coupled with a unit rotation identification scheme. Identifying narrative surprises in central bank communication using this type of data and identification provides surprise measures that are uncorrelated with conventional monetary policy surprises, and, in contrast to such surprises, have a significant effect on subsequent media coverage. In turn, narrative monetary policy surprises lead to macroeconomic responses similar to what recent monetary policy literature associates with the information component of monetary policy communication. Our study highlights the importance of written central bank communication and the role of the media as information intermediaries.